Boreas v1.3.0 - a package for industrial deployment of machine-learned turbulent mixing models for film cooling (formerly known as RaFoFC)
Author: Pedro M. Milani (email: pmmilani@stanford.edu)
Last modified: 06/26/2020
Developed and tested in Python 3.7
Installation
To install, run the following command from this directory:
pip install -e .
To uninstall, run the following from anywhere:
pip uninstall boreas
The commands above will also install some dependencies (included in the file "requirements.txt") needed for this package. Make sure pip is installed (it comes with most Python distributions).
Note that the package requires pytecplot to interface with Tecplot files. To install pytecplot, the user must have Tecplot 360 2017 R1 or later installed. Follow the instructions in https://www.tecplot.com/docs/pytecplot/install.html
Usage
After installation, you can just use the following import statement in any Python program:
from boreas.main import printInfo, applyMLModel, produceTrainingFeatures, trainRFModel
To test everything was installed properly, run the following command in a Python script after the import statement above:
printInfo()
The function applyMLModel is called to apply a given trained machine learning model to a Tecplot file containing the solution of the RANS equations with the k-epsilon model. produceTrainingFeatures and trainRFModel are used, in this order, to train a machine learning model given LES/DNS data. See the file test/example_usage.py for a complete example of training and applying a model.
Examples and Testing
The folder test contains a sample Tecplot file and a script that shows how the functions can be called (example_usage.py). After installation, just run the following from within the test folder:
python example_usage.py
The test folder also contains a script with unit tests, meant to run with the pytest library (test_all.py). To run all the tests, just type the following from the root directory:
pytest